BUSINESS CONTEXT: In this project it requires to develop a customer segmentation to define marketing strategy through machine learning techniqe. The sample dataset summarizes the usage behavior of about 9000 active credit card holders during the last 6 months. The file is at a customer level with 18 behavioral variables.
Problems need to address: Advanced data preparation: Build an ‘enriched’ customer profile by deriving “intelligent” KPIs such as:
Monthly average purchase and cash advance amount Purchases by type (one-off, installments) Average amount per purchase and cash advance transaction, Limit usage (balance to credit limit ratio), Payments to minimum payments ratio etc. Advanced reporting: Use the derived KPIs to gain insight on the customer profiles. Identification of the relationships/ affinities between services. Clustering: Apply a data reduction technique factor analysis for variable reduction technique and a clustering algorithm to reveal the behavioural segments of credit card holders Identify cluster characterisitics of the cluster using detailed profiling. Provide the strategic insights and implementation of strategies for given set of cluster characteristics DATA DICTIONARY: CUST_ID: Credit card holder ID BALANCE: Monthly average balance (based on daily balance averages) BALANCE_FREQUENCY: Ratio of last 12 months with balance PURCHASES: Total purchase amount spent during last 12 months ONEOFF_PURCHASES: Total amount of one-off purchases INSTALLMENTS_PURCHASES: Total amount of installment purchases CASH_ADVANCE: Total cash-advance amount PURCHASES_ FREQUENCY: Frequency of purchases (Percent of months with at least one purchase) ONEOFF_PURCHASES_FREQUENCY: Frequency of one-off-purchases PURCHASES_INSTALLMENTS_FREQUENCY: Frequency of installment purchases CASH_ADVANCE_ FREQUENCY: Cash-Advance frequency AVERAGE_PURCHASE_TRX: Average amount per purchase transaction CASH_ADVANCE_TRX: Average amount per cash-advance transaction PURCHASES_TRX: Average amount per purchase transaction CREDIT_LIMIT: Credit limit PAYMENTS: Total payments (due amount paid by the customer to decrease their statement balance) in the period MINIMUM_PAYMENTS: Total minimum payments due in the period. PRC_FULL_PAYMEN: Percentage of months with full payment of the due statement balance TENURE: Number of months as a customer DATA AVAILABLE: CC GENERAL.csv